2022-04-14 08:51:07

Acknowledgements

  • Support from NICHD, NIH OD, NIMH, NIDA, OBSSR, NSF
  • Karen Adolph, Cathie Tamis-LeMonda, Orit Hertzberg, Tiger Teng

Overview

  • What is PLAY
  • Why PLAY
  • Challenges to face
  • Challenges met
  • Challenges yet-to-be-met
  • A preview

What is PLAY

  • 1,000 mother-infant dyads (12-, 18-, 24-mos)
  • 1 hr natural behavior (video)
  • 5 min structured play (video)
  • House tour (video)
  • Parent-report questionnaires
  • Ambient sound levels

  • Foundational video coding passes
    • Speech & language
    • Emotional expression
    • Object interaction
    • Locomotion & physical activity

  • Common, shared data
  • Rigorous QA control
  • Investigator-specific questions…
  • Dataset as deliverable
  • Catalyze/expand capacity to exploit video

Why PLAY

Natural behavior

Big data developmental science

Open science

The advancement of detailed and diverse knowledge about the development of the world’s children is essential for improving the health and well-being of humanity. The Society for Research in Child Development (SRCD) regards scientific integrity, transparency, and openness as essential for the conduct of research and its application to practice and policy. These values apply to research conduct, to the teaching of scientific methods, and to the translation of science into practice and policy.

Challenges to face

Sampling

  • Age range(s)
  • What language backgrounds
  • Who to include
  • Where to sample
  • What to vary, what to keep constant…
  • Is ‘an hour in the life’ representative?
  • What survey questions & how to collect
  • What behaviors to code

Challenges met

  • 12-mo-olds, 18-mo-olds, & 24-mo-olds
  • Only English and Spanish-speaking households
  • Mom and child
  • 31 sites

Races reported in PLAY counties

Races reported in PLAY counties

Ethnicity reported in PLAY counties

Ethnicity reported in PLAY counties

Languages spoken in PLAY counties

Languages spoken in PLAY counties

Educational attainment in PLAY counties

Educational attainment in PLAY counties

Household income in PLAY counties

Household income in PLAY counties

Survey questions

  • Health
  • Patient Health Questionnaire (PHQ-4)
  • Locomotor milestones
  • MacArthur-Bates CDI

  • Early Childhood Behavior Questionnaire (Rothbart)
  • Media use
  • Pets
  • Household structure
  • Typical day

Behaviors to code

Challenges yet-to-be-met

  • Findable, usable beyond launch group
  • Limitations of Databrary 1.0
    • Virtual volumes?
  • Versioning data, protocol, coding scheme
  • Add-on, follow-up studies
    • New data
    • Augmented, new video annotations
  • COVID-19

A preview

Databrary

Databrary access levels

1-hour natural play

House walk-through

Structured play

Parent-report questionnaires

Load PLAY survey data

databraryapi::login_db("myemail@university.edu")

play_data <- databraryapi::read_csv_data_as_df(session_id = 51539, asset_id = 366382)

Demographics

xtabs(formula = ~ child_sex + age_group, data = play_data) %>%
  knitr::kable(., format = 'html') %>%
  kableExtra::kable_classic(.)
12mo 18mo 24mo
female 12 13 6
male 8 11 18

xtabs(formula = ~ child_race + child_ethnicity, data = play_data) %>%
  knitr::kable(., format = 'html') %>%
  kableExtra::kable_classic(.)
Hispanic or Latino Not Hispanic or Latino
Asian 0 1
Black or African American 1 0
More than one 9 6
Other 0 2
White 4 45

Locomotor milestones

Feeding

Typical behavior?

xtabs(formula = ~ typical_behavior + age_group, data = typical_data) %>%
  knitr::kable(., format = 'html') %>%
  kableExtra::kable_classic(.)
12mo 18mo 24mo
no 1 5 0
yes 18 18 24

Typical night/morning?

xtabs(formula = ~ typical_nightmorning + age_group, data = typical_data) %>%
  knitr::kable(., format = 'html') %>%
  kableExtra::kable_classic(.)
12mo 18mo 24mo
no 6 3 3
yes 13 21 21
## [1] TRUE

Take homes

Assuming a realistic range of prior probabilities for null hypotheses, false report probability is likely to exceed 50% for the whole literature.

  • Big data developmental science of natural behavior is possible & necessary
  • Cognition and emotion in context
  • Ambition and vision drive innovation
  • Future-orientation (what will future researchers want to know) challenging, but invigorating
  • What do we want our science to be about?

Resources

This talk was produced on 2022-04-14 in RStudio using R Markdown and the ioslides framework. The code and materials used to generate the slides may be found at https://github.com/PLAY-behaviorome/2022-04-21-team-sci-cds/. Information about the R Session that produced the code is as follows:

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## [77] mime_0.12          xtable_1.8-4       broom_0.7.11       databraryapi_0.2.7
## [81] later_1.3.0        viridisLite_0.4.0  ellipsis_0.3.2

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Yarkoni, T. (2020). The generalizability crisis. The Behavioral and Brain Sciences, 1–37. https://doi.org/10.1017/S0140525X20001685